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Automatic detection of ischemia in ECG
Noremberczyk, Adam ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
This thesis discusses the utilization of the artificial neural networks (ANN) for detection of coronary artery disease (CAD) in frequency area. The first part of this thesis is orientated towards the theoretical knowledge. Describes the issue of ECG pathological changes. ECQ are converted to frequency area. Described statistical methods and methods for automatic detection of CAD and MI. Explained the issue of the perceptron and ANN. The second deals with use of Neural Network Toolbox MATLAB®. This part focuses on counting and finding suitable parameters and making connection of band. At the end of the thesis UNS is used to detect ischemic parameters and the results are discussed. Average values for the best settings are 100% accuracy.
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Calculating disparity map from color stereo images
Kulíková, Barbora ; Nováček, Petr (referee) ; Klečka, Jan (advisor)
This bachelor’s thesis deals with a creation of the depth maps. The first chapter concerns with the physiology of a human space perception and the methods of displaying the 3D content which are the topics closely related to the depth map, its creation and practical usage. Subsequently, there is a chapter focused on the description of the used methods of the image processing. The fundamental theoretical chapter deals with the methods of computing the disparity and used principles. In the practical part of the thesis an application has been made with a user interface in the Matlab environment. The application enables the user to create the disparity maps through the local and global methods. The functionalism of the application and the implementation of the methods are experimentaly verified. An experiment comparing the methods and analyzing influence of the local method parameters on the quality of the depth map has been made. The last part of the thesis was to create a simple stereopicture database.
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Automatic detection of ischemia in ECG using artificial neural network
Noremberczyk, Adam ; Smital, Lukáš (referee) ; Ronzhina, Marina (advisor)
This thesis discusses the utilization of the artificial neural networks (ANN) as electrocardiography (ECG) classifiers of coronary artery disease (CAD) and myocardial infarction (MI) in ECG signal. The first part of this thesis is orientated towards the theoretical knowledge and describes the issue of ECG pathological changes, methods for automatic detection of CAD and MI and the issue of the perceptron and ANN. The second deals with use of Neural Network Toolbox MATLAB® version R2010a. In graphical user interface development environment (Guide) is created application that is used to compare the success of automatic detection of ischemia in ECG using ANN. It allows the user to set various parameter settings UNS and display ECG waveforms.
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Localization of individual opioid receptor subtypes in CNS
Lišháková, Michaela ; Hejnová, Lucie (advisor) ; Bendová, Zdeňka (referee)
In last decades, the research focused on opioid receptors has been intensively conducted in order to determine their role in various homeostatic functions, control of movement, neurotransmission and drug addiction. An important factor determining the pharmacologic role of opioid receptors is their distribution within the brain regions as well as at the cellular level. Over the past 40 years, a great deal of information concerning their distribution in the central nervous system has been collected, allowing us to determine their localization and mechanisms of their action. In general, results obtained from previous studies are in agreement. However, there are some inconsistencies that impede the accurate determination of receptor distribution and need to be clarified. This paper aims to summarize results of the previously published studies observing the localization of opioid receptors in the rat CNS. Emphasis is placed on the comparison of results obtained by all available methods.
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Automatic detection of ischemia in ECG using artificial neural network
Noremberczyk, Adam ; Smital, Lukáš (referee) ; Ronzhina, Marina (advisor)
This thesis discusses the utilization of the artificial neural networks (ANN) as electrocardiography (ECG) classifiers of coronary artery disease (CAD) and myocardial infarction (MI) in ECG signal. The first part of this thesis is orientated towards the theoretical knowledge and describes the issue of ECG pathological changes, methods for automatic detection of CAD and MI and the issue of the perceptron and ANN. The second deals with use of Neural Network Toolbox MATLAB® version R2010a. In graphical user interface development environment (Guide) is created application that is used to compare the success of automatic detection of ischemia in ECG using ANN. It allows the user to set various parameter settings UNS and display ECG waveforms.
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|
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Calculating disparity map from color stereo images
Kulíková, Barbora ; Nováček, Petr (referee) ; Klečka, Jan (advisor)
This bachelor’s thesis deals with a creation of the depth maps. The first chapter concerns with the physiology of a human space perception and the methods of displaying the 3D content which are the topics closely related to the depth map, its creation and practical usage. Subsequently, there is a chapter focused on the description of the used methods of the image processing. The fundamental theoretical chapter deals with the methods of computing the disparity and used principles. In the practical part of the thesis an application has been made with a user interface in the Matlab environment. The application enables the user to create the disparity maps through the local and global methods. The functionalism of the application and the implementation of the methods are experimentaly verified. An experiment comparing the methods and analyzing influence of the local method parameters on the quality of the depth map has been made. The last part of the thesis was to create a simple stereopicture database.
|
|
|
Automatic detection of ischemia in ECG
Noremberczyk, Adam ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
This thesis discusses the utilization of the artificial neural networks (ANN) for detection of coronary artery disease (CAD) in frequency area. The first part of this thesis is orientated towards the theoretical knowledge. Describes the issue of ECG pathological changes. ECQ are converted to frequency area. Described statistical methods and methods for automatic detection of CAD and MI. Explained the issue of the perceptron and ANN. The second deals with use of Neural Network Toolbox MATLAB®. This part focuses on counting and finding suitable parameters and making connection of band. At the end of the thesis UNS is used to detect ischemic parameters and the results are discussed. Average values for the best settings are 100% accuracy.
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